Value Creation with the Modern Data Stack

WebinarMarch 2023

As organizations of all sizes continuously look to drive value out of data, the modern data stack has emerged as a clear solution for getting insights into the hands of the organization. With the rapid pace of innovation not slowing down, the tools within the modern data stack have enabled data teams to drive faster insights, collaborate at scale, and democratize data knowledge. However, are tools just enough to drive business value with data? Join Yali Sassoon, CSO and Co-Founder at Snowplow Analytics and Barr Moses, CEO and Co-Founder of Monte Carlo Data as they outline how data leaders can drive value creation with data in 2023.

Summary

Studying the potential of the modern data stack, the dialogue between industry professionals Bar Moses and Yali Sassoon at Datacamp Radar 2023 investigates the challenges of achieving return on investment (ROI) amidst economic instability. They highlight that while advanced data tools are important, they alone are not sufficient to drive value. The discussion underscores the need to align data teams closely with business goals and measure their contribution through meaningful KPIs. In addition, they discuss how data teams can effectively define high-value use cases and the future of the modern data stack, particularly with the rise of generative AI. As the conversation progresses, a recurring theme surfaces: the need for data teams to utilize advanced tools, and also to cultivate a business-oriented mindset to truly capitalize on data initiatives.

Key Takeaways:

Link data team activities closely with business goals for maximum impact.
Gauge the ROI of data projects using well-defined KPIs and impact scorecards.
Concentrate on high-impact use cases to effectively drive data value.
Anticipate the modern data stack to progress, integrating more AI solutions.
Adopt a product mindset for data projects to enhance customer influence.

Deep Dives

Aligning Data Teams with Business Goals

Successfully extracting value from data projects requires data teams to closely align with the core goals of their organizations. Bar Moses emphasizes that data teams often fall into the trap of becoming isolated, functioning as support entities rather than strategic partners. She notes, "Successful data t ...
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eams tie themselves to important company projects," highlighting the need for teams to integrate their efforts with key business goals. By doing so, data teams can ensure they are contributing to impactful projects, such as new product launches, customer retention efforts, or personalized recommendations, thereby enhancing their organizational influence.

Gauging ROI in Data Projects

One of the primary challenges for data teams today is proving the ROI of their projects. Moses suggests a structured approach to this challenge, proposing the use of a framework to map data projects against business value. This includes identifying key areas where data projects can increase operational efficiencies or uncover new opportunities. Yali Sassoon adds that data teams should focus on outcomes that directly impact revenue or cost reductions, citing examples like JetBlue's data-driven efforts to optimize flight operations. Establishing clear metrics for success, such as time to insight or data reliability, allows teams to demonstrate their value in quantifiable terms.

Focusing on High-Impact Use Cases

For data teams to maximize their impact, prioritizing high-impact use cases is essential. Sassoon advocates for a use-case-first approach, where the business need dictates the technology employed. He warns against the anti-pattern of assembling technology stacks without clear business goals, which can lead to significant costs without tangible benefits. By identifying strategic use cases, such as optimizing marketing campaigns or enhancing customer experience, data teams can effectively demonstrate their value and secure buy-in from business stakeholders.

Future of the Modern Data Stack

Looking ahead, the future of the modern data stack is poised for significant evolution, particularly with advancements in AI. Moses and Sassoon predict that AI and BI tools will increasingly converge, offering more integrated solutions for data-driven decision-making. As the complexity of the data ecosystem grows, there will be a greater emphasis on smooth integration between tools, reducing the burden on data teams to manage disparate systems. The speakers also see a future where data becomes even more central to business operations, with organizations investing in scalable, reliable data infrastructure to maintain competitive advantage.